In this work, we introduce a new method ability radial basic function-partial least square (RBF-PLS) with high accuracy and precision in QSPR studies. Three quantitative structure-propertty ...
Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression using the C# language. NW kernel regression is simple to implement and is ...
The water inrush is one of the most catastrophic emergencies in metro tunnels. To avoid the potential water inrush, this paper proposes a risk assessment model for the metro tunnel based on Delphi ...
Radial Basis Function Neural Networks (RBFNNs) are a type of neural network that combines elements of clustering and function approximation, making them powerful for both regression and classification ...
First at all, thanks a lot for putting this nice tool available for everyone. It is really nice! I have a question regarding which RBF basis to choose in case I am interested in obtaining smooth ...
It has been proven that robot-assisted rehabilitation training can effectively promote the recovery of upper-limb motor function in post-stroke patients. Increasing patients’ active participation by ...
ABSTRACT: Accurately approximating higher order derivatives is an inherently difficult problem. It is shown that a random variable shape parameter strategy can improve the accuracy of approximating ...
Abstract: In order to provide design guidelines for energy efficient 6G networks, we propose a novel radial basis function (RBF) based optimization framework to maximize the integrated relative energy ...
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